System, Method, and Computer Program Product for Detecting Redundancies in Information Provided by Customers in a Customer Service System

ABSTRACT

The present invention provides a system, method, and computer program product for automatically detecting any unnecessary repetition by customers of specific types of information in a multi-channel (e.g., self-service application, IVR system, live agent center) customer service session. For each channel used in the customer service session, the information provided by the customer in the channel is recorded in a log, transcription, or other record. The record(s) for the customer service session are subsequently parsed for specific types of information provided by the customer. From the parsed records, specific types of information provided by the customer in two or more channels during the customer service session are identified. In one embodiment, the results are analyzed to determine if providing such information in two or more channels is redundant, and, if so, this is counted as a redundancy.

BACKGROUND OF THE INVENTION

1. Field of the Invention

This invention relates generally to customer service systems, and, more particularly, to detecting redundancies in information provided by customers in a customer service system.

2. Description of the Background Art

Many customer service systems have multiple channels to communicate with customers. During a customer service session, a customer may be transferred from one channel to another channel. For example, a customer may call into an IVR system and then be transferred to a live agent center. Alternately, a customer may use a self-service application provided by a customer service system and then connect with an IVR system or live agent. During a single customer service session, customers are sometimes asked to provide the same information in different channels. For example, a user may be asked by both an IVR system and a live agent to provide his account number. This redundancy often increases the length of the customer service session and frustrates customers. Consequently, it is desirable to be able to automatically detect when customers are asked to unnecessarily repeat information in a multi-channel customer service session. Detecting such redundancies will help an application designer create a better application dialog/flow that eliminates such redundancies, thereby increasing customer satisfaction.

SUMMARY

The present invention provides a system, method, and computer program product for automatically detecting any unnecessary repetition by customers of specific types of information in a multi-channel customer service session. The customer service system creates a record of information provided by a customer via a first channel within the customer service system. If the customer service session is transferred to a second channel, the customer service system also creates a record of information provided by the customer during the customer service session via the second channel.

The record associated with the first channel is parsed for specific types of information provided by the customer via the first channel during the customer service session. Similarly, the record associated with the second channel is also parsed for specific types of information provided by the customer via the second channel during the customer service session.

From the parsed records, specific types of information provided by the customer in both the first and second channels during the customer service session are identified. In one embodiment, the results are analyzed to determine if providing such information in both channels was redundant, and, if so, this is counted as a redundancy. Such information may be used by an application designer to design a better application or dialog that eliminates or reduces requesting redundant information from a customer

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a flowchart that illustrates an automated method for detecting the unnecessary repetition of specific types of information in a customer service session according to one embodiment of the present invention.

FIG. 2 is a block diagram of an example customer service system according to one embodiment of the invention.

FIG. 3 is a screen shot of an example report illustrates the percentage of calls to an IVR system/live agent with repeated information.

FIG. 4 is a screen shot of an example report that lists individual customer service sessions and any redundant information provided during a customer service session.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

FIG. 2 illustrates an example of a customer service system. Customer service system 200 includes three channels via which a customer can communicate with the system 200. The customer may communicate with the system via a self-service software application 250, such as a mobile handset application or a web application, an IVR system 210, or a live agent center 215. Those skilled in the art will appreciate that a customer service system may include less or more channels. Customer service system 200 is just an example and the invention is not limited to this system. The other illustrated elements of system 200 will be described later.

FIG. 1 illustrates an automated method for detecting the unnecessary repetition of specific types of information in a customer service session that is transferred from a first channel within a customer service system to a second channel within the customer service system. The customer service system creates a record of information provided by a customer via a first channel within the customer service system (step 110). In response to a user request or for other reasons, the customer is transferred to a second channel within the customer service system (step 120). The customer service system creates a record of information provided by the customer during the customer service session via the second channel (step 130).

The customer service system aggregates the records from the first and second channels for the customer service session (135). The record associated with the first channel is then parsed for specific types of information provided by the customer via the first channel during the customer service session (step 140). The record associated with the second channel is also parsed for specific types of information provided by the customer via the second channel during the customer service session (step 150).

From the parsed records, any specific type of information provided by the customer in both the first and second channels during the customer service session is identified (step 160). The parsed information is analyzed to determine if providing such information in both channels was redundant, and, if so, this is counted as a redundancy (step 165). A report is generated for a set of customer service sessions indicating specific types of information that were redundantly provided by customers in both the first and second channels (step 170).

During a customer service session, a customer may be transferred to a third channel in the customer service system. The above-described method is not limited to finding repetition across two channels. A record is created for each channel in which a customer provides information, and each record may be parsed to identify whether specific types of information are repeated by the customer in multiple channels (e.g., records from three or more channels may be compared).

Examples of specific types of information for which the records may be parsed include phone number, social security number, pin, password, name, credit card number, and account number.

In one embodiment, records from an IVR system and live agent center are in the form of transcripts that are created by transcribing audio recordings of the customer, IVR system, and live agent. In the preferred embodiment, audio recordings in the IVR channel and live agent channel are stereo recordings in which the customer, agent, and/or IVR system are on different audio streams.

In one embodiment, records from a self-service software application, such as a web application or a mobile handset application, are in the form of logs.

The example customer service system illustrated in FIG. 2 includes a Session Aggregation Module 260, an Information Redundancy Module (IRM) 220, and a Report Generator 230. The Session Aggregation Module 260 aggregates records from a single customer service session that spanned two or more channels. For example, if the customer called into the IVR system and then was transferred to a live agent, the Session Aggregation Module 260 aggregates the records (i.e., the transcriptions) from IVR system 210 and the Agent Center 215 for the applicable customer service session.

Records across multiple channels may simply be aggregated or they may be combined into one record. If a single record is maintained across multiple channels, then, for logs, the separation between channels is logged, or, for transcriptions, the transcription is parsed for the separation point.

The Information Redundancy Module (IRM) 220 identifies the specific types of information that were provided by a customer in two or more channels during a single customer service session. In one embodiment, the IRM 220 maintains a count of the number of times a specific type of information was provided by the customer during the customer service session.

The IRM 220 includes an application log parser 235, a semantic parser 230, and an Analyzer 225. The semantic parser 230 parses transcriptions for specific types of information. The parsing is performed using grammars, semantic rules, or statistical models input by a system administrator. The grammars are rules to parse textual information to identify named entities (i.e., the specific types of information). The statistical models are models trained on labeled text data to automatically detect named entities.

The application log parser 235 parses logs. If the logs contain unstructured data from which the log parser 235 has to mine the specific types of information, the application log parser may use grammars or statistical models to parse the logs. If the logs have structured data that clearly mentions the specific types of information for which the log parser is looking, then application log parser likely can parse the logs without using grammars or statistical models.

The Analyzer 225 analyzes the parsed results to determine whether information repeated during a customer service session is redundant. The logic used to determine the redundancy can be controlled using rules provided to the Analyzer 225. In one embodiment, the inputs to the Analyzer include the following:

-   -   A unique customer service session ID for each customer service         session analyzed     -   Relevant metadata from each customer service sessions, such as         channel types used in the customer service session (e.g., IVR,         AGENT, WEB, MOZBILE, etc.), time-stamps, application who data         the Analyzer 225 is analyzing (e.g., application for Company         ABC), etc.     -   Parsed information. This is the output of the application log         parser 235 and/or semantic parser 230     -   Rules that describe the logic to measure redundancy

Below are examples of the type of rules that may be used by the Analyzer:

-   -   1) Rule: Do not count multiple occurrences of specific types of         information within the same channel as a redundancy.         -   The above rule ensures that redundancy is only counted             across channels. Under this rule, redundancies within a             channel are ignored.     -   2) Rule: A valid count should be comprised of both a question         and a response. This rule ensures that both sides of an         interaction are considered in validating a single count. For         example, if the IVR systems says “Please give me your 10 digit         social security number,” the rule ensures that, the customer did         indeed provide the 10 digit social security number before         associating “social security number” with one count.     -   3) Rule: Consider two different specific types of information as         the same information.         -   This rule ensures that Analyzer 225 combines the counts of             two different types of information to determine redundancy.             For example, assume the rule specifies that Account # and             Phone # should be counted as the same information. If a             customer provides Account # to an IVR system and a live             agent later asks for Phone #, the Analyzer will count this             as a valid redundancy (if implementing this rule).

The above rules are only examples, and other types of rules may be applied.

The Report Generator 230 generates reports based on the output of the IRM 220. For example, the Report Generator 230 may generate a report that specifies the percentage of customer service sessions with redundancies. FIG. 3 is an example of such a report. This figure illustrates the percentage of calls to an IVR system where the customer provided a specific type of information (i.e., SSN, PIN, PHONE, CCN, ACCOUNT NUM, and ADDRESS) to both the IVR system and a live agent.

FIG. 4 illustrates an example of another type of report that may be generated by the Report Generator 230. This report covers a set of customer service sessions. For each customer service session, the report lists any specific types of information that were repeated across two different channels by the customer. In FIG. 4, the report shows that there were two customer service sessions where customers had to redundantly provide their phone number at least twice and two customer services sessions where customers had redundantly provide their pin at least twice.

The term customer as used herein includes customers, prospective customers, and other users of customer service systems.

As will be understood by those familiar with the art, the invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. Accordingly, the above disclosure of the present invention is intended to be illustrative and not limiting of the invention. 

1. An automated method for detecting the repetition of specific types of information in a customer service session that is transferred from a first channel within a customer service system to a second channel within the customer-service system, the method comprising: creating a record of the information provided by the customer during a customer service session via a first channel within the customer service system; transferring the customer service session to a second channel within the customer service system; creating a record of the information provided by the customer during the customer service session via the second channel; parsing the record associated with the first channel for specific types of information provided by the customer during the customer service session; parsing the record associated with the second channel for specific types of information provided by the customer during the customer service session; and identifying any of the specific types of information that were provided by the customer in both the first channel and the second channel.
 2. The method of claim 1, further comprising: transferring the customer service session to a third channel within the customer service system; creating a record of the information provided by the customer during the customer service session via the third channel; parsing the record associated with the third channel for specific types of information provided by the customer during the customer service session; and identifying any of the specific types of information that were provided by the customer in both (i) the third channel and (ii) the first or second channel.
 3. The method of claim 2, wherein the first, second, and third channels are each one of the following: an IVR system, a live agent communication center, and a self-service software application.
 4. The method of claim 1, wherein one of the first and second channels is an IVR system.
 5. The method of claim 1, wherein one of the first and second channels is a live agent communication center.
 6. The method of claim 1, wherein one of the first and second channels is a self-service software application on a mobile platform.
 7. The method of claim 1, wherein one of the first and second channels is a web application.
 8. The method of claim 1, wherein one or more of the records is a transcription.
 9. The method of claim 7, wherein a semantic parser is used to parse transcriptions.
 10. The method of claim 1, wherein one or more of the records is a log.
 11. The method of claim 9, wherein a log parser is used to parse the logs.
 12. The method of claim 1, further comprising creating a report encompassing a plurality of customer service sessions that that indicates the specific types of information that were provided by customers in both the first and second channels.
 13. The method of claim 1, further comprising: for a set of customer service sessions, identifying, for each of the specific types of information, the percentage of calls in the set for which the specific type of information was provided by customers in both the first and second channels.
 14. The method of claim. 1, further comprising prior to the parsing step: aggregating the record for the first channel with the record for the second channel.
 15. A system for detecting the repetition of specific types of information in a customer service session that is transferred between at least two channels in a customer service system, the system comprising: a first customer service subsystem for providing a customer service session via the first channel and for creating a record of information provided by a customer via the first channel during such customer service session; a second customer service subsystem for providing a customer service session via the second channel and for creating a record of information provided by a customer via the second channel during such customer service session; a session aggregator, operatively couple to both the first customer service subsystem and the second customer service subsystem, for aggregating records for customer service sessions that are transferred between the first channel and the second channel; one or more parsers for receiving aggregated records from the session aggregator and, for each customer service session transferred between the first channel and second channel, parsing the records for such customer service session for specific types of information provided by a customer during such customer service session; and an analyzer for receiving the output from the parser(s) and identify any of the specific types of information that were provided by a customer in both the first and second channels during a single customer service session.
 16. The system of claim 15, further comprising a report generating module for creating reports that identify specific types of information provided by a customer in both the first and second channels in a single customer service session.
 17. The system of claim 15, wherein one of the first and second subsystems is an IVR system.
 18. The system of claim 15, wherein one of the first and second subsystems is a live-agent communication center.
 19. The system of claim 15, wherein one of the first and second subsystems is a server that serves a self-service mobile application on a mobile device.
 20. The system of claim 15, wherein one of the first and second subsystems is a server that provides a self-service web application.
 21. The system of claim 15, wherein at least one parser is a log parser.
 22. The system of claim 15, wherein at least one parser is a semantic parser.
 23. The system of claim 15, wherein, in response to identifying one or more specific types of information that were provided in both the first and second channels, the analyzer applies one or more rules to determine whether providing such information in both channels was redundant.
 24. A computer program embodied on a computer-readable medium and comprising code, that, when executed by a computer system, enables the computer system to perform the following method: creating a record of the information provided by the customer during a customer service session via a first channel within the customer service system; transferring the customer service session to a second channel within the customer service system; creating a record of the information provided by the customer during the customer service session via the second channel; parsing the record associated with the first channel for specific types of information provided by the customer during the customer service session; parsing the record associated with the second channel for specific types of information provided by the customer during the customer service session; and identifying any of the specific types of information that were provided by the customer in both the first channel and the second channel.
 25. The method of claim 1, further comprising: in response to identifying one or more specific types of information that were provided in both the first and second channels, determining whether providing such information in both channels was redundant.
 26. The computer program of claim 24, further comprising: in response to identifying one or more specific types of information that were provided in both the first and second channels, determining whether providing such information in both channels was redundant. 